Pharmacokinetic/Pharmacodynamic Background and Methods and Scientific Evidence Base for Dosing of Second-line Tuberculosis Drugs

Population Pharmacokinetics of Tigecycline for Critically Ill Patients Undergoing Continuous Renal Replacement Therapy

Background

Tigecycline is considered one of the last resorts for treating infections caused by multidrug-resistant bacteria. Continuous renal replacement therapy (CRRT) is widely used in critically ill patients, especially those with acute kidney injury or severe infections. However, pharmacokinetic data for tigecycline in patients receiving CRRT are limited.

Methods

This was a single-center prospective clinical study with intensive sampling that included critically ill patients who received tigecycline and CRRT. A population pharmacokinetic (PPK) model was developed and evaluated by goodness-of-fit plots, bootstrap analysis, visual predictive checks, and numerical predictive checks. Pharmacokinetic/pharmacodynamic target attainment and cumulative fraction of response analyses were performed to explore the potential need for dose adjustments of tigecycline in CRRT.

Results

In total, 21 patients with 167 concentrations were included. A two-compartment model adequately described the tigecycline concentration-time points, but no covariates were found to adequately explain the viability in the pharmacokinetic parameters of tigecycline. The typical values of CL, Q, V1 and V2 were 4.42 L/h, 34.8 L/h, 30.9 L and 98.7 L, respectively. For most infections, the standard regimen of 50 mg/12 h was deemed appropriate, expect for skin and soft skin tissue infections and community-acquired pneumonia caused by Acinetobacter baumannii and Klebsiella pneumoniae, which required a dosage regimen of 100 mg/12 h or higher.

Conclusion

A tigecycline PPK model describing critically ill patients undergoing CRRT was successfully developed. The optimized dosage regimens for various infections are recommended.

Meropenem-vaborbactam restoration of first-line drug efficacy and comparison of meropenem-vaborbactam-moxifloxacin versus BPaL MDR-TB regimen

BACKGROUND

Meropenem in combination with β-lactamase inhibitors (BLIs) and other drugs was tested to identify alternative treatment regimens for multidrug-resistant tuberculosis (MDR-TB).

METHODS

The following were performed: (1) MIC experiments; (2) static time-kill studies (STKs) with different BLIs; and (3) a hollow fibre model system of TB (HFS-TB) studies with meropenem-vaborbactam combined with human equivalent daily doses of 20 mg/kg or 35 mg/kg rifampin, or moxifloxacin 400 mg, or linezolid 600 mg vs. bedaquiline-pretonamid-linezolid (BPaL) for MDR-TB. The studies were performed using Mycobacterium tuberculosis (M. tuberculosis) H37Rv and an MDR-TB clinical strain (named M. tuberculosis 16D) that underwent whole genome sequencing. Exponential decline models were used to calculate the kill rate constant (K) of different HFS-TB regimens.

RESULTS

Whole genome sequencing revealed mutations associated with resistance to rifampin, isoniazid, and cephalosporins. The meropenem-vaborbactam MIC of M. tuberculosis was H37Rv 2 mg/L and > 128 mg/L for M. tuberculosis 16D. Relebactam and vaborbactam improved both the potency and efficacy of meropenem in STKs. Meropenem-vaborbactam alone failed to kill M. tuberculosis 16D but killed below day 0 burden when combined with isoniazid and rifampin, with the moxifloxacin combination being the most effective and outranking bedaquiline and pretomanid. In the HFS-TB, meropenem-vaborbactam-moxifloxacin and BPaL had the highest K (log10 cfu/mL/day) of 0.31 (95% CI 0.17-0.58) and 0.34 (95% CI 0.21-0.56), while meropenem-vaborbactam-rifampin (35 mg/kg) had a K of 0.18 (95% CI 0.12-0.25). The K for meropenem-vaborbactam-moxifloxacin-linezolid demonstrated antagonism.

CONCLUSION

Adding meropenem-vaborbactam could potentially restore the efficacy of isoniazid and rifampin against MDR-TB. The meropenem-vaborbactam-moxifloxacin backbone regimen has implications for creating a new effective MDR-TB regimen.

Omadacycline pharmacokinetics/pharmacodynamics in the hollow fiber model and clinical validation of efficacy to treat pulmonary Mycobacterium abscessus disease

BACKGROUND

Guideline-based therapy (GBT) for pulmonary Mycobacterium abscessus (Mab) disease achieves sustained sputum culture conversion (SSCC) rates of 30%; this is reflected by poor efficacy of GBT in the hollow fiber system model of Mab (HFS-Mab), which killed ∼1.22 log10 CFU/mL. This study was performed to determine which clinical dose of omadacycline, a tetracycline antibiotic, should be used in combination therapy to treat pulmonary Mab disease for relapse-free cure.

METHODS

First, omadacycline intrapulmonary concentration-time profiles of seven daily doses were mimicked in the HFS-Mab model and exposures associated with optimal efficacy were identified. Second, 10,000 subject Monte-Carlo simulations were performed to determine whether oral omadacycline 300 mg/day achieved these optimal exposures. Third, a retrospective clinical study on omadacycline vs. primarily tigecycline-based salvage therapy was conducted to assess rates of SSCC and toxicity. Fourth, a single patient was recruited to validate the findings.

RESULTS

Omadacycline efficacy in the HFS-Mab was 2.09 log10 CFU/mL at exposures achieved in >99% of patients on 300 mg/day omadacycline. In the retrospective study of omadacycline 300 mg/day-based combinations vs. comparators, SSCC was achieved in 8/10 vs. 1/9 (P=0.006), symptom improvement in 8/8 vs. 5/9 (P=0.033), toxicity in 0 vs. 9/9 (P<0.001), and therapy discontinuation due to toxicity in 0 vs. 3/9 (P<0.001) cases, respectively. In one prospectively recruited patient, omadacycline 300 mg/day salvage therapy achieved SSCC and symptom-resolution in 3 months.

CONCLUSION

Based on the preclinical and clinical data, omadacycline 300 mg/day in combination regimens could be appropriate for testing in Phase III trials in patients with Mab pulmonary disease.

Advances in the design of combination therapies for the treatment of tuberculosis

INTRODUCTION

Tuberculosis requires lengthy multi-drug therapy. Mycobacterium tuberculosis occupies different tissue compartments during infection, making drug access and susceptibility patterns variable. Antibiotic combinations are needed to ensure each compartment of infection is reached with effective drug treatment. Despite drug combinations' role in treating tuberculosis, the design of such combinations has been tackled relatively late in the drug development process, limiting the number of drug combinations tested. In recent years, there has been significant progress using in vitro, in vivo, and computational methodologies to interrogate combination drug effects.

AREAS COVERED

This review discusses the advances in these methodologies and how they may be used in conjunction with new successful clinical trials of novel drug combinations to design optimized combination therapies for tuberculosis. Literature searches for approaches and experimental models used to evaluate drug combination effects were undertaken.

EXPERT OPINION

We are entering an era richer in combination drug effect and pharmacokinetic/pharmacodynamic data, genetic tools, and outcome measurement types. Application of computational modeling approaches that integrate these data and produce predictive models of clinical outcomes may enable the field to generate novel, effective multidrug therapies using existing and new drug combination backbones.

Pharmacokinetics and pharmacodynamics of anti-tuberculosis drugs: An evaluation of in vitro, in vivo methodologies and human studies

There has been an increased interest in pharmacokinetics and pharmacodynamics (PKPD) of anti-tuberculosis drugs. A better understanding of the relationship between drug exposure, antimicrobial kill and acquired drug resistance is essential not only to optimize current treatment regimens but also to design appropriately dosed regimens with new anti-tuberculosis drugs. Although the interest in PKPD has resulted in an increased number of studies, the actual bench-to-bedside translation is somewhat limited. One of the reasons could be differences in methodologies and outcome assessments that makes it difficult to compare the studies. In this paper we summarize most relevant in vitro, in vivo, in silico and human PKPD studies performed to optimize the drug dose and regimens for treatment of tuberculosis. The in vitro assessment focuses on MIC determination, static time-kill kinetics, and dynamic hollow fibre infection models to investigate acquisition of resistance and killing of Mycobacterium tuberculosis populations in various metabolic states. The in vivo assessment focuses on the various animal models, routes of infection, PK at the site of infection, PD read-outs, biomarkers and differences in treatment outcome evaluation (relapse and death). For human PKPD we focus on early bactericidal activity studies and inclusion of PK and therapeutic drug monitoring in clinical trials. Modelling and simulation approaches that are used to evaluate and link the different data types will be discussed. We also describe the concept of different studies, study design, importance of uniform reporting including microbiological and clinical outcome assessments, and modelling approaches. We aim to encourage researchers to consider methods of assessing and reporting PKPD of anti-tuberculosis drugs when designing studies. This will improve appropriate comparison between studies and accelerate the progress in the field.

Delamanid Resistance: Update and Clinical Management

Delamanid, a-first-in-class bicyclic nitroimidazole, was recently approved for multidrug-resistant tuberculosis treatment. Pitted against the hope for improving treatment outcomes is the threat of the rapid resistance emergence. This review provides information on the mechanisms of action, resistance emergence, and drug susceptibility testing (DST) for delamanid. Delamanid resistance has already been reported in both in vitro experiments and clinical settings. Although mutations conferring delamanid resistance have been identified in fbiA, fbiB, fbiC, ddn, and fgd1 genes of Mycobacterium tuberculosis, knowledge about the molecular resistance mechanisms is limited, and there remains no standardized DST method. The rapid acquisition of delamanid resistance emphasizes the need for optimal use of new drugs, the need for drug resistance surveillance, and a comprehensive understanding of drug resistance mechanisms. Further studies are necessary to investigate genetic and phenotypic changes that determine clinically relevant delamanid resistance to help develop a rapid delamanid DST.

Higher Dosing of Rifamycins Does Not Increase Activity against Mycobacterium tuberculosis in the Hollow-Fiber Infection Model

Improvements in the translational value of preclinical models can allow more-successful and more-focused research on shortening the duration of tuberculosis treatment. Although the hollow-fiber infection model (HFIM) is considered a valuable addition to the drug development pipeline, its exact role has not been fully determined yet. Since the strategy of increasing the dose of rifamycins is being evaluated for its treatment-shortening potential, additional in vitro modeling is important. Therefore, we assessed increased dosing of rifampin and rifapentine in our HFIM in order to gain more insight into the place of the HFIM in the drug development pipeline. Total and free-fraction concentrations corresponding to daily dosing of 2.7, 10, and 50 mg of rifampin/kg of body weight, as well as 600 mg and 1,500 mg rifapentine, were assessed in our HFIM using the Mycobacterium tuberculosis H37Rv strain. Drug activity and the emergence of drug resistance were assessed by CFU counting and subsequent mathematical modeling over 14 days, and pharmacokinetic exposures were checked. We found that increasing rifampin exposure above what is expected with the standard dose did not result in higher antimycobacterial activity. For rifapentine, only the highest concentration showed increased activity, but the clinical relevance of this observation is questionable. Moreover, for both drugs, the emergence of resistance was unrelated to exposure. In conclusion, in the simplest experimental setup, the results of the HFIM did not fully correspond to preexisting clinical data. The inclusion of additional parameters and readouts in this preclinical model could be of interest for proper assessment of the translational value of the HFIM.

Population Pharmacokinetics and Bayesian Dose Adjustment to Advance TDM of Anti-TB Drugs

Tuberculosis (TB) is still the number one cause of death due to an infectious disease. Pharmacokinetics and pharmacodynamics of anti-TB drugs are key in the optimization of TB treatment and help to prevent slow response to treatment, acquired drug resistance, and adverse drug effects. The aim of this review was to provide an update on the pharmacokinetics and pharmacodynamics of anti-TB drugs and to show how population pharmacokinetics and Bayesian dose adjustment can be used to optimize treatment. We cover aspects on preclinical, clinical, and population pharmacokinetics of different drugs used for drug-susceptible TB and multidrug-resistant TB. Moreover, we include available data to support therapeutic drug monitoring of these drugs and known pharmacokinetic and pharmacodynamic targets that can be used for optimization of therapy. We have identified a wide range of population pharmacokinetic models for first- and second-line drugs used for TB, which included models built on NONMEM, Pmetrics, ADAPT, MWPharm, Monolix, Phoenix, and NPEM2 software. The first population models were built for isoniazid and rifampicin; however, in recent years, more data have emerged for both new anti-TB drugs, but also for defining targets of older anti-TB drugs. Since the introduction of therapeutic drug monitoring for TB over 3 decades ago, further development of therapeutic drug monitoring in TB next steps will again depend on academic and clinical initiatives. We recommend close collaboration between researchers and the World Health Organization to provide important guideline updates regarding therapeutic drug monitoring and pharmacokinetics/pharmacodynamics.

Ethionamide population pharmacokinetics/pharmacodynamics and therapeutic implications in South African adult patients with drug-resistant tuberculosis

INTRODUCTION

Ethionamide is part of the drug-resistant tuberculosis regimen whose pharmacokinetic (PK) and pharmacodynamic (PD) information is limited. The aim of the study was to describe the PK and simulate doses to assess PD attainment.

METHODS

This was an observational population PK study of patients admitted for drug-resistant tuberculosis at a hospital in South Africa. Nonlinear mixed-effects modelling implemented in Monolix 2019R2 was used to estimate population pharmacokinetic parameters. We performed Monte Carlo simulations to assess and optimise the dose regimen. The target C_max range was 2.5-5 μg/mL, which is within the minimum inhibitory concentration (MIC) range. The target AUC_0-24h was 140.5 μg*h/mL, which corresponds to the PK/PD target ratio AUC_0-24h /MIC of 56.2.

RESULTS

A one-compartment pharmacokinetic model with a lag-time, first-order absorption and elimination best described the PK of ethionamide. The lag-time, absorption rate constant (ka), volume of distribution (V/F) and clearance (Cl/F) were 0.66 hours, 0.434 h^-1 , 180 L and 99.5 L/h, respectively, for a typical individual weighing 52.6 kg. Between-subject variability in lag-time, ka, V/F and Cl/F were 38%, 92%, 168% and 120%, respectively. Simulation of the recommended doses of 15-20 mg/kg, 500 mg, 750 mg and 1000 mg for patients in the weight bands <33, 33-50, 51-70 and >70 kg resulted in <17% and 3% of the patients achieving the target C_max and AUC_0-24h , respectively.

CONCLUSION

There is high variability in ethionamide PK and very few patients attain the desired target exposure at standard or optimised doses. We propose individualised dose regimen optimisation.

Integrating Pharmacokinetics and Pharmacodynamics in Operational Research to End Tuberculosis

Tuberculosis (TB) elimination requires innovative approaches. The new Global Tuberculosis Network (GTN) aims to conduct research on key unmet therapeutic and diagnostic needs in the field of TB elimination using multidisciplinary, multisectorial approaches. The TB Pharmacology section within the new GTN aims to detect and study the current knowledge gaps, test potential solutions using human pharmacokinetics informed through preclinical infection systems, and return those findings to the bedside. Moreover, this approach would allow prospective identification and validation of optimal shorter therapeutic durations with new regimens. Optimized treatment using available and repurposed drugs may have an increased impact when prioritizing a person-centered approach and acknowledge the importance of age, gender, comorbidities, and both social and programmatic environments. In this viewpoint article, we present an in-depth discussion on how TB pharmacology and the related strategies will contribute to TB elimination.

How to design a study to evaluate therapeutic drug monitoring in infectious diseases?

BACKGROUND

Therapeutic drug monitoring (TDM) is a tool to personalize and optimize dosing by measuring the drug concentration and subsequently adjusting the dose to reach a target concentration or exposure. The evidence to support TDM is however often ranked as expert opinion. Limitations in study design and sample size have hampered definitive conclusions of the potential added value of TDM.

OBJECTIVES

We aim to give expert opinion and discuss the main points and limitations of available data from antibiotic TDM trials and emphasize key elements for consideration in design of future clinical studies to quantify the benefits of TDM.

SOURCES

The sources were peer-reviewed publications, guidelines and expert opinions from the field of TDM.

CONTENT

This review focuses on key aspects of antimicrobial TDM study design: describing the rationale for a TDM study, assessing the exposure of a drug, assessing susceptibility of pathogens and selecting appropriate clinical endpoints. Moreover we provide guidance on appropriate study design.

IMPLICATIONS

This is an overview of different aspects relevant for the conduct of a TDM study. We believe that this paper will help researchers and clinicians to design and conduct high-quality TDM studies.

Pharmacokinetic Modeling, Simulation, and Development of a Limited Sampling Strategy of Cycloserine in Patients with Multidrug-/Extensively Drug-Resistant Tuberculosis

BACKGROUND AND OBJECTIVE

Multidrug-resistant tuberculosis has much poorer treatment outcomes compared with drug-susceptible tuberculosis because second-line drugs for treating multidrug resistant tuberculosis are less effective and are frequently associated with side effects. Optimization of drug treatment is urgently needed. Cycloserine is a second-line tuberculosis drug with variable pharmacokinetics and thus variable exposure when programmatic doses are used. The objective of this study was to develop a population pharmacokinetic model of cycloserine to assess drug exposure and to develop a limited sampling strategy for cycloserine exposure monitoring.

MATERIAL AND METHODS

Patients with multidrug-/extensively drug-resistant tuberculosis who were treated for > 7 days with cycloserine were eligible for inclusion. Patients received cycloserine 500 mg (body weight ≤ 50 kg) or 750 mg (body weight > 50 kg) once daily. MW/Pharm 3.83 (Mediware, Groningen, The Netherlands) was used to parameterize the population pharmacokinetic model. The model was compared with pharmacokinetic values from the literature and evaluated with a bootstrap analysis, Monte Carlo simulation, and an external dataset. Monte Carlo simulations were used to develop a limited sampling strategy.

RESULTS

Cycloserine plasma concentration vs time curves were obtained from 15 hospitalized patients (nine male, six female, median age 35 years). Mean dose/kg body weight was 11.5 mg/kg (standard deviation 2.04 mg/kg). Median area under the concentration-time curve over 24 h (AUC_0-24 h) of cycloserine was 888 h mg/L (interquartile range 728-1252 h mg/L) and median maximum concentration of cycloserine was 23.31 mg/L (interquartile range 20.14-33.30 mg/L). The final population pharmacokinetic model consisted of the following pharmacokinetic parameters [mean (standard deviation)]: absorption constant K_{a_po} of 0.39 (0.31) h^-1, distribution over the central compartment (V_d) of 0.54 (0.26) L/kg LBM, renal clearance as fraction of the estimated glomerular filtration rate of 0.092 (0.038), and metabolic clearance of 1.05 (0.75) L/h. The population pharmacokinetic model was successfully evaluated with a bootstrap analysis, Monte Carlo simulation, and an external dataset of Chinese patients (difference of 14.6% and 19.5% in measured and calculated concentrations and AUC_0-24 h, respectively). Root-mean-squared-errors found in predicting the AUC_0-24 h using a one- (4 h) and a two- (2 h and 7 h) limited sampling strategy were 1.60% and 0.14%, respectively.

CONCLUSIONS

This developed population pharmacokinetic model can be used to calculate cycloserine concentrations and exposure in patients with multidrug-/extensively drug-resistant tuberculosis. This model was successfully validated by internal and external validation methods. This study showed that the AUC_0-24 h of cycloserine can be estimated in patients with multidrug-/extensively drug-resistant tuberculosis using a 1- or 2-point limited sampling strategy in combination with the developed population pharmacokinetic model. This strategy can be used in studies to correlate drug exposure with clinical outcome. This study also showed that good target attainment rates, expressed by time above the minimal inhibitory concentration, were obtained for cycloserine with a minimal inhibitory concentration of 5 and 10 mg/L, but low rates with a minimal inhibitory concentration of 20 and 32.5 mg/L.

Amikacin Dosing for MDR Tuberculosis: A Systematic Review to Establish or Revise the Current Recommended Dose for Tuberculosis Treatment

Background

Amikacin has been used for over 40 years in multidrug resistant tuberculosis (MDR-TB), but there is still debate on the right dose. The aim of this review was to search relevant pharmacokinetic (PK) and pharmacodynamic (PD) literature for the optimal dose and dosing frequency of amikacin in MDR-TB regimens trying to optimize efficacy while minimizing toxicity.

Methods

A systematic review on the value of amikacin as second-line drug in the treatment of MDR-TB was performed.

Results

Five articles were identified with data on PK, hollow-fiber system model for TB and or early bactericidal activity of amikacin. Despite the long period in which amikacin has been available for the treatment of MDR-TB, very little PK data is available. This highlights the need for more research.

Conclusions

Maximum concentration (Cmax) of amikacin related to MIC proved to be the most important PK/PD index for efficacy. The target Cmax/MIC ratio should be 10 at site of infection. Cumulative area under the concentration-time curve (AUC) corresponding with cumulative days of treatment was associated with an increased risk of toxicity.

Gatifloxacin Pharmacokinetics/Pharmacodynamics-based Optimal Dosing for Pulmonary and Meningeal Multidrug-resistant Tuberculosis

Background

Gatifloxacin is used for the treatment of multidrug-resistant tuberculosis (MDR-TB). The optimal dose is unknown.

Methods

We performed a 28-day gatifloxacin hollow-fiber system model of tuberculosis (HFS-TB) study in order to identify the target exposures associated with optimal kill rates and resistance suppression. Monte Carlo experiments (MCE) were used to identify the dose that would achieve the target exposure in 10000 adult patients with meningeal or pulmonary MDR-TB. The optimal doses identified were validated using probit analyses of clinical data from 2 prospective clinical trials of patients with pulmonary and meningeal tuberculosis. Classification and regression-tree (CART) analyses were used to identify the gatifloxacin minimum inhibitory concentration (MIC) below which patients failed or relapsed on combination therapy.

Results

The target exposure associated with optimal microbial kill rates and resistance suppression in the HFS-TB was a 0-24 hour area under the concentration-time curve-to-MIC of 184. MCE identified an optimal gatifloxacin dose of 800 mg/day for pulmonary and 1200 mg/day for meningeal MDR-TB, and a clinical susceptibility breakpoint of MIC ≤ 0.5 mg/L. In clinical trials, CART identified that 79% patients failed therapy if MIC was >2 mg/L, but 98% were cured if MIC was ≤0.5 mg/L. Probit analysis of clinical data demonstrated a >90% probability of a cure in patients if treated with 800 mg/day for pulmonary tuberculosis and 1200 mg/day for meningeal tuberculosis. Doses ≤400 mg/day were suboptimal.

Conclusions

Gatifloxacin doses of 800 mg/day and 1200 mg/day are recommended for pulmonary and meningeal MDR-TB treatment, respectively. Gatifloxacin has a susceptible dose-dependent zone at MICs 0.5-2 mg/L.

Treatment of Drug-Resistant Tuberculosis. An Official ATS/CDC/ERS/IDSA Clinical Practice Guideline

Background: The American Thoracic Society, U.S. Centers for Disease Control and Prevention, European Respiratory Society, and Infectious Diseases Society of America jointly sponsored this new practice guideline on the treatment of drug-resistant tuberculosis (DR-TB). The document includes recommendations on the treatment of multidrug-resistant TB (MDR-TB) as well as isoniazid-resistant but rifampin-susceptible TB.Methods: Published systematic reviews, meta-analyses, and a new individual patient data meta-analysis from 12,030 patients, in 50 studies, across 25 countries with confirmed pulmonary rifampin-resistant TB were used for this guideline. Meta-analytic approaches included propensity score matching to reduce confounding. Each recommendation was discussed by an expert committee, screened for conflicts of interest, according to the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology.Results: Twenty-one Population, Intervention, Comparator, and Outcomes questions were addressed, generating 25 GRADE-based recommendations. Certainty in the evidence was judged to be very low, because the data came from observational studies with significant loss to follow-up and imbalance in background regimens between comparator groups. Good practices in the management of MDR-TB are described. On the basis of the evidence review, a clinical strategy tool for building a treatment regimen for MDR-TB is also provided.Conclusions: New recommendations are made for the choice and number of drugs in a regimen, the duration of intensive and continuation phases, and the role of injectable drugs for MDR-TB. On the basis of these recommendations, an effective all-oral regimen for MDR-TB can be assembled. Recommendations are also provided on the role of surgery in treatment of MDR-TB and for treatment of contacts exposed to MDR-TB and treatment of isoniazid-resistant TB.

Quantitative assessment of the activity of antituberculosis drugs and regimens

Introduction: Identification of optimal drug doses and drug combinations is crucial for optimized treatment of tuberculosis. Areas covered: An unprecedented level of research activity involving multiple approaches is seeking to improve tuberculosis treatment. This report is a review of the quantitative methods currently used on clinical data sets to identify drug exposure targets and optimal drug combinations for tuberculosis treatment. A high-level summary of the methods, including the strengths and weaknesses of each method and potential methodological improvements is presented. Methods incorporating data generated from multiple sources such as in vitro and clinical studies, and their potential to provide better estimates of pharmacokinetic/pharmacodynamic (PK/PD) targets, are discussed. PK/PD relationships identified are compared between different studies and data analysis methods. Expert opinion: The relationships between drug exposures and tuberculosis treatment outcomes are complex and require analytical methods capable of handling the multidimensional nature of the relationships. The choice of a method is guided by its complexity, interpretability of results, and type of data available.

Multiparameter Responses to Tedizolid Monotherapy and Moxifloxacin Combination Therapy Models of Children With Intracellular Tuberculosis

Background

Children are often neglected during early development of antituberculosis agents, and most receive treatment after it is first tested in adults. However, very young children have tuberculosis that differs in many respects from adult cavitary pneumonia and could have different toxicity profiles to drugs. Linezolid is effective against intracellular tuberculosis, a common manifestation in young children. However, linezolid has considerable toxicity due to inhibition of mitochondrial enzymes. Tedizolid could be a replacement if it shows equal efficacy and reduced toxicity.

Methods

We performed tedizolid dose-effect studies in the hollow fiber system model of intracellular tuberculosis. We measured linezolid concentrations, colony-forming units (CFU), time-to-positivity, and monocyte viability and performed RNA sequencing on infected cells collected from repetitive sampling of each system. We also compared efficacy of tedizolid vs linezolid and vs tedizolid-moxifloxacin combination.

Results

There was no downregulation of mitochondrial enzyme genes, with a tedizolid 0-24 hour area under the concentration-time curve (AUC0-24) of up to 90 mg*h/L. Instead, high exposures led to increased mitochondrial gene expression and monocyte survival. The AUC0-24 to minimum inhibitory concentration ratio associated with 80% of maximal bacterial kill (EC80) was 184 by CFU/mL (r2 = 0.96) and 189 by time-to-positivity (r2 = 0.99). Tedizolid EC80 killed 4.0 log10 CFU/mL higher than linezolid EC80. The tedizolid-moxifloxacin combination had a bacterial burden elimination rate constant of 0.27 ± 0.05 per day.

Conclusions

Tedizolid demonstrated better efficacy than linezolid, without the mitochondrial toxicity gene or cytotoxicity signatures encountered with linezolid. Tedizolid-moxifloxacin combination had a high bacterial elimination rate.

Ethionamide Pharmacokinetics/Pharmacodynamics-derived Dose, the Role of MICs in Clinical Outcome, and the Resistance Arrow of Time in Multidrug-resistant Tuberculosis

Background

Ethionamide is used to treat multidrug-resistant tuberculosis (MDR-TB). The antimicrobial pharmacokinetics/pharmacodynamics, the contribution of ethionamide to the multidrug regimen, and events that lead to acquired drug resistance (ADR) are unclear.

Methods

We performed a multidose hollow fiber system model of tuberculosis (HFS-TB) study to identify the 0-24 hour area under the concentration-time curve (AUC0-24) to minimum inhibitory concentration (MIC) ratios that achieved maximal kill and ADR suppression, defined as target exposures. Ethionamide-resistant isolates underwent whole-genome and targeted Sanger sequencing. We utilized Monte Carlo experiments (MCEs) to identify ethionamide doses that would achieve the target exposures in 10000 patients with pulmonary tuberculosis. We also identified predictors of time-to-sputum conversion in Tanzanian patients on ethionamide- and levofloxacin-based regimens using multivariate adaptive regression splines (MARS).

Results

An AUC0-24/MIC >56.2 was identified as the target exposure in the HFS-TB. Early efflux pump induction to ethionamide monotherapy led to simultaneous ethambutol and isoniazid ADR, which abrogated microbial kill of an isoniazid-ethambutol-ethionamide regimen. Genome sequencing of isolates that arose during ethionamide monotherapy revealed mutations in both ethA and embA. In MCEs, 20 mg/kg/day achieved the AUC0-24/MIC >56.2 in >95% of patients, provided the Sensititre assay MIC was <2.5 mg/L. In the clinic, MARS revealed that ethionamide Sensititre MIC had linear negative relationships with time-to-sputum conversion until an MIC of 2.5 mg/L, above which patients with MDR-TB failed combination therapy.

Conclusions

Ethionamide is an important contributor to MDR-TB treatment regimens, at Sensititre MIC <2.5 mg/L. Suboptimal ethionamide exposures led to efflux pump-mediated ADR.

Levofloxacin Pharmacokinetics/Pharmacodynamics, Dosing, Susceptibility Breakpoints, and Artificial Intelligence in the Treatment of Multidrug-resistant Tuberculosis

Background

Levofloxacin is used for the treatment of multidrug-resistant tuberculosis; however the optimal dose is unknown.

Methods

We used the hollow fiber system model of tuberculosis (HFS-TB) to identify 0-24 hour area under the concentration-time curve (AUC0-24) to minimum inhibitory concentration (MIC) ratios associated with maximal microbial kill and suppression of acquired drug resistance (ADR) of Mycobacterium tuberculosis (Mtb). Levofloxacin-resistant isolates underwent whole-genome sequencing. Ten thousands patient Monte Carlo experiments (MCEs) were used to identify doses best able to achieve the HFS-TB-derived target exposures in cavitary tuberculosis and tuberculous meningitis. Next, we used an ensemble of artificial intelligence (AI) algorithms to identify the most important predictors of sputum conversion, ADR, and death in Tanzanian patients with pulmonary multidrug-resistant tuberculosis treated with a levofloxacin-containing regimen. We also performed probit regression to identify optimal levofloxacin doses in Vietnamese tuberculous meningitis patients.

Results

In the HFS-TB, the AUC0-24/MIC associated with maximal Mtb kill was 146, while that associated with suppression of resistance was 360. The most common gyrA mutations in resistant Mtb were Asp94Gly, Asp94Asn, and Asp94Tyr. The minimum dose to achieve target exposures in MCEs was 1500 mg/day. AI algorithms identified an AUC0-24/MIC of 160 as predictive of microbiologic cure, followed by levofloxacin 2-hour peak concentration and body weight. Probit regression identified an optimal dose of 25 mg/kg as associated with >90% favorable response in adults with pulmonary tuberculosis.

Conclusions

The levofloxacin dose of 25 mg/kg or 1500 mg/day was adequate for replacement of high-dose moxifloxacin in treatment of multidrug-resistant tuberculosis.

Transformation Morphisms and Time-to-Extinction Analysis That Map Therapy Duration From Preclinical Models to Patients With Tuberculosis: Translating From Apples to Oranges

Background

A major challenge in medicine is translation of preclinical model findings to humans, especially therapy duration. One major example is recent shorter-duration therapy regimen failures in tuberculosis.

Methods

We used set theory mapping to develop a computational/modeling framework to map the time it takes to extinguish the Mycobacterium tuberculosis population on chemotherapy from multiple hollow fiber system model of tuberculosis (HFS-TB) experiments to that observed in patients. The predictive accuracy of the derived translation transformations was then tested using data from 108 HFS-TB Rapid Evaluation of Moxifloxacin in Tuberculosis (REMoxTB) units, including 756 colony-forming units (CFU)/mL. Derived transformations, and Latin hypercube sampling-guided simulations were used to predict cure and relapse after 4 and 6 months of therapy. Outcomes were compared to observations, in 1932 patients in the REMoxTB clinical trial.

Results

HFS-TB serial bacillary burden and serial sputum data in the derivation dataset formed a structure-preserving map. Bactericidal effect was mapped with a single step transformation, while the sterilizing effect was mapped with a 3-step transformation function. Using the HFS-TB REMoxTB data, we accurately predicted the proportion of patients cured in the 4-month REMoxTB clinical trial. Model-predicted vs clinical trial observations were (i) the ethambutol arm (77.0% [95% confidence interval {CI}, 74.4%-79.6%] vs 77.7% [95% CI, 74.3%-80.9%]) and (ii) the isoniazid arm (76.4% [95% CI, 73.9%-79.0%] vs 79.5% [95% CI, 76.1%-82.5%]).

Conclusions

We developed a method to translate duration of therapy outcomes from preclinical models to tuberculosis patients.